This paper addresses bearing-only three-dimensional target localization using three cooperative UAVs under observation inconsistency and degraded geometry. A weighted point-to-line least-squares localization model is established to fuse multiple line-of-sight (LOS) observations derived from image measurements, camera calibration, and UAV poses. To handle unreliable measurements without ground truth, a reliability assessment mechanism is developed by combining geometric stability indicators with observation consistency metrics, enabling weak geometry and abnormal observations to be identified online. Based on this assessment, an adaptive optimization framework is introduced to perform residual-driven adaptive weighting and configuration optimization, thereby suppressing unreliable LOS measurements and improving the conditioning of cooperative geometry. Simulation results under four representative scenarios show that the proposed method consistently improves localization accuracy and robustness. The mean localization error is reduced from 0.545 m to 0.260 m under abnormal observations, from 0.355 m to 0.081 m under degraded geometry, and from 0.711 m to 0.280 m when both effects occur simultaneously. Statistical evaluations including RMSE, standard deviation, maximum error, confidence intervals, and box-plot analysis further demonstrate that the proposed framework effectively reduces error dispersion and improves robustness.

In multi-UAV bearing-only active tracking, the estimation and control performance is fundamentally determined by the target-centered bearing geometry, as passive angle-of-arrival measurements provide directional information without direct range information. To overcome this limitation, this paper formulates the problem as prescribed-shell bearing-geometry self-organization, in which the radial sensing scale is regulated to an admissible shell while the angular bearing distribution is actively reshaped on that shell. A shell-compatible moment–volume bearing-enclosure potential is first constructed directly on unit bearing directions, decoupling angular geometry improvement from unsafe range reduction and encoding directed balance, angular isotropy, and noncoplanar enclosure. To realize the resulting direction-space descent via physical UAV motion, a radius-normalized tangential lifting mechanism is derived from bearing-direction kinematics, eliminating radius-dependent angular-rate bias. The nominal radial–tangential command is then executed through a bearing-geometry-preserving ECBF-QP that embeds a predefined-time radial shell-reaching constraint, enforces target standoff, inter-UAV separation, and input constraints, and preserves shell reaching and tangential geometry improvement whenever feasible. Closed-loop analysis establishes shell reaching, practical bearing-geometry descent, safety forward invariance, and signal boundedness. Finally, improved bearing geometry, prescribed-shell convergence, preserved safety margins, reduced disruption from safety filtering, and real-world implementability are demonstrated via simulations, ablation studies, ROS-based validation, and a real-world flight experiment, which provide a promising approach for multi-UAV bearing-only active tracking.